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Graph Marketing Defined

Graph Marketing is a strategy that places customers and their networks of influence at the center of marketing and advertising by leveraging their social identities, conversations, and communities.

Graph Marketing is a strategy that places customers and their networks of influence at the center of marketing and advertising by leveraging their social identities, conversations, and communities.

For those of you who are familiar with Eric Fisher and Facebook’s Social Design Principals, the above should sound familiar. I simply have taken the framework that they have pushed developers to follow when building apps and applied it broadly to the marketing and advertising industry.. Why? I think it’s a perfect summation of the parts that make up Graph Marketing. In short:

Utilize personal information and connections to make advertising creative and marketing experiences a personalized experience.

Show conversations, social context, and activity everywhere within your marketing ecosystem.

Make it really easy to talk, share, give feedback, and engage with your brand and its fans & followers.

NOTE: This is my fist attempt at a definition. In no way do I suggest that this is the final. Consider the above as a working definition to help generate dialog, criticism, and feedback that will ultimately produce a more accurate and lasting understanding of this concept.

Why?

THE MOVE FROM THE LINEAR FUNNEL TO THE CUSTOMER DECISION JOURNEY (CDJ): The classic marketing funnel that suggested there was a narrowing array of decisions and choices until purchase has been replaced by a dynamic Customer Decision Journey (CDJ). The CDJ model,conceived by David Edelman – McKinsey&Company, suggests that today’s customers take a more complex iterative path thru and beyond purchase (See “Consider the Honey When Attracting Your Social Customers“). Within the CDJ, customers really emphasize the input of those who define their graphs. Brian Solis from Altimeter Group states “(customers) evaluate the shared experiences of those they trust, and expect business to respond to their socialized questions”. As a consequence, these customer’s follow an elliptical pattern, vs a linear approach, in their decision making.

As customers move around the CDJ “their next steps are inspired by the insights of others, and their experience are, in turn, fed back into the cycle to inform the decisions of others”. This activity is represented by a secondary path within CDJ called The Influence Loop (see illustration below). The Influence Loop is made up of a tapestry of interest graphs, search graphs, and social graphs, etc. These networks play an instrumental role in how customers conduct pre-commerce research and how they express their commerce and post-commerce experiences.

BIG DATA & DATA CONNECTEDNESS: A major by product of the CDJ is a mountain of decentralized real-time data (likes, tweets, tags, check-ins, etc) from social, mobile and sensor systems. This data is connected to consumers, their geographical location, their friends and families, and to their things. This, in turn, has created the field of Big Data and the introduction of new Graph Databases. Data scientists have stepped in to further help organizations efficiently capture, visualize and derive intelligence from this information. Facebook, Google, Twitter, and LinkedIn are employing armies of data scientists to help unlock their network’s potential, create better experiences for users, and develop new products. Brands will need their own for similar reasons.

ACCESS TO GRAPHS: Today, we are witnessing major social networks provide new ways to access their users collection of graphs. In an effort to show that they are capable of monetizing their networks, they have rolled out a number of new ad units that are available via their web and mobile touch points. Facebook’s Open Graph is informing real-time advertising via Action Spec Targeting and Open Graph Sponsored Stories. Eventually, Facebook could leverage their newly launched Graph Search to offer sponsored results, search query targeting, relevant offers and retargeting. Google, which made its fortune from monetizing indexed content on the web, is now applying social graph, interest graph, and semantic data to search results with the objective of predicting users intent, resulting in even more valuable (and effective) SEM inventory. Twitter has introduced keyword targeting to their platform. This means that brands and others can now plan and serve ads to users based on specific words in users’ tweets. Twitter says the service is rolling out across all of its ad network, mobile and desktop, covering 15 languages and all markets where it currently serves Twitter Ads. Additionally, they have opened its advertising API to third parties, which will let larger advertisers create more sophisticated Interest Graph campaigns on Twitter.

How?

MAKE GRAPHS CENTRAL TO YOUR MARKETING MIX: Today, major networks like Facebook and Google offer access to audiences that rival major broadcast and print channels. Opportunities to engage with customers in real-time are becoming abundant due to rapid marketplace innovations. Additionally, micro-networks are on the rise. In many cases, these small niche communities will play a more critical role to some industries (i.e. health care, personal finance, etc) than the large ones. Each network (regardless of big or small) introduces different paid and organic opportunities. Make it a priority to understand which graphs impact your enterprise, how they connect, and who are the real influencers in each. Waste no time in establishing these graphs as the engine to your marketing machine.

DESIGN SYSTEMS: Stop trying to make heavy weight marketing destinations within networks. Instead, create agile/light systems that follow the principals of social design and maximize your brands ability to increase its share of fans/followers, likes and positive feedback. Additionally, embed graphs intimately into your web and app ecosystems via social login. Done correctly, this will create a better experience for your customers and optimize what you are doing via graph display and graph search paid advertising.

DEVELOP NETWORKING SKILLS: It goes without saying that networks are everywhere. Your brand has many internal and external networks. You personally have social and interest based networks. Understanding how these all should work together is a major priority. Providing the necessary training to your staff and deploying the right tool sets to manage distributed network presences across the enterprise is a good place to start.

LEVERAGE BIG DATA AND DATA SCIENCE: Your company (regardless of its size) is generating Big Data. Avoid being data-rich and insight-poor by not appropriating the right amount of resources to engage data scientists. These individuals should be full-time members of your marketing team as they will ensure that you are capturing big data correctly and deriving the maximum amount of intelligence (via statistics, modeling, & visualization).

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Author Profile

Jeremi Karnell has been a leader in the digital marketing space since the dawn of the web as we know it. As the web has evolved over the past 16 years Jeremi has consistently been ahead of the curve in helping businesses adapt and profit from digital interaction with their customers. It was Jeremi who recognized the need for a new type of agency and began to assemble the founding team that would become beehaus in 2012. As CEO, his leadership and vision have helped make beehaus one of the nation's premiere agencies for graph based and distributed touch point social marketing.
A quick peak at Jeremi's Pinterest page reveals a passion for design and a borderline obsession with cute bulldogs. Beware: Jeremi is prone to extreme anxiety when exposed to Yo Gabba Gabba videos.

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